Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

In this paper, we investigate the predictive ability of three sentiment indices constructed by
social media, newspaper, and Internet media news to forecast the realized volatility (RV) of …

Summary We move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by
adding the how. The current forecasting literature has focused on matching specific …

In this study, we examine the long-term predictive role of the global financial stress index
(GFSI) on equity market volatility and provide a comprehensive analysis using GFSI for the …

The main goal of this paper is to investigate the predictability of five economic uncertainty
indices for oil price volatility in a changing world. We employ the standard predictive …

In this paper, we compare the predictive ability between forecast combination and shrinkage
method in the prediction of oil price volatility. Our investigation is based on the …

Inspired by the commonly held view that international stock market volatility is equivalent to
cross‐market information flow, we propose various ways of constructing two types of …

This paper focuses on distinguishing the predictive power of five newly developed
uncertainty indices, that is, global and US economic policy uncertainty (GEPU and US EPU) …

This study extends the HAR-RV model to detailedly compare the role of leverage effects,
jumps, and overnight information in predicting the realized volatilities (RV) of 21 …

To improve the predictability of crude oil futures market returns, this paper proposes a new
combination approach based on principal component analysis (PCA). The PCA combination …